A Model for the Determination of Pollen Count Using Google Search Queries for Patients Suffering from Allergic Rhinitis

Table 1

Results of cross-correlations for the Aachen study centre.

	Subgroup 1; Averaged CSMS; (𝑛=16)				Subgroup 2; IgE ≥ class III (3.5 kU/L); (𝑛=8)				Subgroup 2; IgE < class III (3.5 kU/L); (𝑛=8)				Subgroup 4; CSMS ≥ 50% of mean; (𝑛=13)				Subgroup 4; CSMS < 50% of mean; (𝑛=3)
	CCF	lag	SE	𝑃 value	CCF	lag	SE	𝑃 value	CCF	lag	SE	𝑃 value	CCF	lag	SE	𝑃 value	CCF	lag	SE	𝑃 value
Grass pollen count Bonn	0.466	−1	0.107	<0.001	0.441	6	0.110	<0.001	0.386	−1	0.107	<0.001	0.461	−1	0.107	<0.001	0.395	7	0.111	<0.001
Grass pollen count Mönchengladbach	0.630	0	0.107	<0.001	0.607	0	0.107	<0.001	0.412	−7	0.111	<0.001	0.622	0	0.107	<0.001	0.339	3	0.108	<0.01
Keyword-combination (1) NRW	0.643	−1	0.106	<0.001	0.517	−1	0.106	<0.001	0.645	−1	0.106	<0.001	0.607	−1	0.106	<0.001	0.486	1	0.106	<0.001
Keyword-combination (2) NRW	0.715	−1	0.106	<0.001	0.608	−1	0.106	<0.001	0.622	−1	0.106	<0.001	0.688	−1	0.106	<0.001	0.420	1	0.106	<0.001